Hybrid renewable energy system design using multobjective optimization

The aim of this work is to present a comparative study between different structures of hybrid renewable energy systems (HRES). Three main combinations of photovoltaique (PV), wind turbine (WT), diesel generators (DG) and battery bank (BT) are considered in order to present to the system designer all possibilities he can need as basic data to make decision. For each scenario, we investigate multi-objective genetic algorithm to optimize simultaneously the annualized system cost (ASC) and the reliability, which is represented by renewable energy fraction (REF) and the Loss-of-Load Probability (LOLP) considered as the operating time of the diesel generator. The proposed method was applied to the analysis of HRES which can supply either remote village or industrial areas. The decision variables included in the optimization process are the power to install of PV array and wind turbine, battery bank number and diesel generator rated power.